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- Abstract：To comprehensively elucidate the current status and application potential of genomic selection （GS） in crop genetic improvement and breeding， a total of 253 publications from Web of Science and CNKI were retrieved by using “genomic selection”， “crop breeding”， “deep learning” and “statistical models” as keywords. This study systematically summarized research progress in theoretical foundations， methodological evolution， model optimization， application cases， and outstanding challenges of GS， and focused on how specific strategies， such as multi-omics integration and neural-network-based approaches， can improve the predictive accuracy of GS-assisted breeding. The results indicate that： GS has expanded from conventional phenotype-based selection theory to modern breeding practices that integrate high-throughput genomic data. Meanwhile， GS models have evolved from early linear statistical approaches centered on best linear unbiased prediction to Bayesian models， regularization methods， multi-trait prediction， genotype-by-environment （G×E） modeling frameworks， and machine-learning and deep-learning models， which have shown marked advantages for predicting complex traits. In addition， major crops such as soybean have become representative systems for applying GS in breeding， encompassing model training， optimizing of training populations， and modeling of G×E interaction. In the future， breakthroughs in GS will depend on multi-omics data integration， robust modeling of environment-genotype interactions， interpretable algorithms， multimodal deep-learning frameworks， and the construction of large-scale training datasets tailored to practical breeding programs. Overall， GS is becoming the key technological pillar of next-generation intelligent breeding systems and providing an important leverage point for achieving genetic gain and sustainable crop improvement under constraints of limited arable land and ongoing climate challenges.Keywords：genomic selection;BLUP;BAYES;machine learning173|94|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To investigate the effects of drought stress on the growth and drought tolerance of foxtail millet （Setaria italica）， this study employed 26 diverse foxtail millet genotypes at the heading-flowering stage. Two treatments，well-watered control （soil moisture maintained at 60% field capacity， CK） and drought stress （soil moisture maintained at 30% to 35% field capacity， DS） were designed during the heading to flowering period. Physiological characteristic of flowering stage and yield traits at maturity were measured. Drought resistances were evaluated using the yield-based drought resistance index （DRI）. The results demonstrated that：Drought stress significantly reduced chlorophyll content， photosynthetic rate （Pn）， maximum photochemical efficiency of PSII （Fv/Fm）， and maximum photochemical energy conversion potential （Fv/F0） across all genotypes. Compared with CK，‘Zhenggu 678’exhibited the smallest reductions in chlorophyll content， photosynthetic rate， and Fv/Fm （decreased by 30.0%， 3.3%， and 1.9%， respectively） under drought conditions， while ‘Yugu 27’ and ‘Yugu 101’ showed minimal decline in Fv/F0 （decreased by 1.3%）. Drought stress remarkably elevated leaf soluble sugar， soluble protein， and proline contents， as well as the activities of superoxide dismutase （SOD）， peroxidase （POD）， and catalase （CAT）. ‘Chiyou Jinmiao 1’ displayed the greatest increase in soluble sugar by 68%. ‘Yugu 29’ showed the highest soluble protein accumulation （37% up）. ‘Gongmi 1’ exhibited the most pronounced increases in proline content （11.40 times） and POD activity （2.16 times）. ‘Jigu 22’ demonstrated the highest SOD activity elevation （1.19 times）， and ‘Jigu 168’ showed maximal CAT activity enhancement （3.33 times）. Based on yield DRI analysis， ‘Zhenggu 678’ （DRI=1.111）， ‘Zhonggu 989’ （DRI=1.192） and ‘Jigu 30’ （DRI=1.144） were identified as genotypes with strong drought resistance. Result of principal component analysis identified the thousand-kernel weight， plant height， photosynthetic rate， Fv/Fm， chlorophyll content， proline content， and SOD enzyme activity as key indicators for assessing drought tolerance at the flowering stage.Keywords：foxtail millet;drought stress;physiological responses;drought resistance evaluation105|27|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To identify drought-related AmMADSs in Agropyron mongolicum Keng， the unigenes obtained from transcriptome sequencing of A. mongolicum under 25% （0.041 7 mol/L） PEG 6 000-simulated drought stress was used as the research object. A total of twelve MADS-box family genes were screened. Bioinformatics methods were used to analyze their physicochemical properties， subcellular localization， conserved motifs， phylogenetic tree， and protein secondary and tertiary structures. Additionally， qRT-PCR technology was employed to examine the expression patterns of MADS-box family genes at 0（CK），1.0， 3.0， 5.0， 7.0 d after 25% （0.0417 mol/L） PEG 6 000 treatment and 1.0 d after rehydration. The results show that： The protein molecular weights of the twelve selected MADS-box transcription factors from A. mongolicum ranges from 7 263.38 to 31 349.53 u， and the length of encoded amino acids ranges from 65 to 273. The theoretical isoelectric points （pI） of the proteins ranges from 5.43 to 11.16. Among which， three MADS-box transcription factors are acidic proteins and nine are basic proteins. The proteins encoded by all twelve A. mongolicum MADS-box genes are localized in the nucleus. They lack transmembrane domains， and contain numerous phosphorylation sites， and their secondary and tertiary structures are primarily composed of random coils and α-helices. Phylogenetic analysis revealed that the A. mongolicum genes， AmMADS26-1， AmMADS26-2， AmMADS29-2， AmMADS47， and AmMADS55 are closely related to known drought-resistant MADS-box family proteins in rice. qRT-PCR results showed that after simulated drought treatment （25% PEG 6，000）， the expression levels of AmMADS26-1， AmMADS26-2， AmMADS29-2， and AmMADS47 increased by 1.55 to 4.55 times at 1.0 d of drought treatment compared to the CK. Among them， the expression patterns of AmMADS26-1 and AmMADS47 showed a downward trend from day 1 to 7 under drought treatment， but their expression levels were still higher than those of CK. In contrast， the expression level of AmMADS55 was 1.57 and 2.28 times higher than that of CK after 3.0 and 5.0 d of drought treatment respectively. In summary， based on bioinformatics analysis and expression pattern identification of the MADS-box gene family in A. mongolicum， this study identified five key genes responsive to drought stress， namely AmMADS26-1， AmMADS26-2， AmMADS29-2， AmMADS47， and AmMADS55.Keywords：Agropyron mongolicum Keng;MADS-box;bioinformatics analysis;drought stress87|22|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：The Erhai Lake Basin is a typical production base for fresh-eating corn cultivation in a plateau lake area of Yunnan Province， where small-holder farming is the dominant mode. In order to explore the application effect and potential risks of different brands of chicken manure fertilizer applied as basal fertilizer in the Erhai Lake Basin， the main fresh-eating corn varieties ‘Nongkenuo 336’， ‘Jingzinuo 219’， ‘SBS902’， and ‘Tianzi 23’ in the Erhai Lake Basin were selected as the test varieties. Four treatments were set up： Brand 1 chicken manure organic fertilizer （T1）， Brand 2 dried chicken manure fertilizer （T2）， Brand 3 dried chicken manure fertilizer （T3） and no fertilizer （CK）. The effects of different brands of chicken manure fertilizer on seed germination characteristics， seedling safety （burnt seedling rate）， key agronomic traits and yield were investigated by split-plot experimental design. The results showed that： 1） The results of leaching solution treatment showed that the germination index of T1 treatment was more than 70%， which met the requirements， while T2 and T3 treatments significantly inhibited seed germination， the germination rate decreased by 6.8% to 27.6% and was lower than that of CK， and the radicle length decreased by 6.9% to 55.7%； After applying chicken manure fertilizer in the field， the burnt seedling rate of T2 and T3 treatments reached 1.3% to 10.7%， which was significantly higher than that of T1 （≤1.1%） and CK （≤0.6%） （P<0.05）. Among all varieties， ‘Tianzi 23’ exhibited a lower seedling burning rate across all treatments compared to the others. 2） The application of three kinds of chicken manure fertilizers in the field increased the plant height， relative chlorophyll content and total dry matter accumulation of fresh-eating corn， and significantly increased the single ear weight and yield of fresh-eating corn （P<0.05）. Among them， the yields of the four fresh-eating corn varieties under T2 treatment were the highest， with an average yield increase of 15.2% to 28.3%， and the average yield increase under T1 and T3 treatments was 5.7% to 19.1%. In summary， the two brands of dried chicken manure fertilizers （T2 and T3） commonly used in the Erhai Lake Basin exhibited a dual effect on fresh-eating corn： high yield potential coexists with seedling-stage risks. This study recommends that small-holder farmers adopt a ‘variety-first’ fertilization strategy： Prioritizing the use of well-rotted， standardized chicken manure organic fertilizer （T1）； Alternatively， using dried chicken manure fertilizer in combination with a stress-tolerant variety ‘Tianzi 23’ to effectively mitigate application risks. This would not only adapt to the actual production needs of small-holder farming， but also provide technical support for the optimization of regional planting-breeding cycles and the collaborative governance of agricultural non-point source pollution.Keywords：Erhai Lake Basin;composted chicken manure;air-dried chicken manure;fresh-eating corn60|28|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To investigate the distribution suitability of sand-fixing plants and their soil moisture vegetation carrying capacity in the agro-pastoral ecotone of Northern China， three tree species （Pinus sylvestris var. mongholica， Elaeagnus angustifolia L.， and Salix matsudana Koidz.） and three shrub species （Haloxylon ammodendron （C. A. Mey.） Bunge， Hippophae rhamnoides L.， and Caragana korshinskii Kom.） were selected as the research subjects. A total of 28 environmental factors and the Maximum Entropy model （MaxEnt） were combined to evaluate the spatial distribution suitability of the above-mentioned sand-fixing plants. This study focused primarily on water limitation conditions， and the carrying capacity model was used to quantify the carrying threshold of each plant species in the suitable area. The results show that the spatial variation of sand-fixing plant suitable areas is significant. Among them： The suitable ranges of Hippophae rhamnoides L.， Salix matsudana Koidz. and Caragana korshinskii Kom.are the widest， accounting for more than 50%， and the three plants are found in the eastern， central， and western regions of the area； Pinus sylvestris var. mongholica and Elaeagnus angustifolia L. have a relatively smaller suitable distribution range， are mainly found in the western and central parts of the study area； In contrast， Haloxylon ammodendron （C. A. Mey.） Bunge has a suitable distribution range that covers only a quarter of the regional area， mainly distributed in the western part of the region. According to the soil moisture vegetation carrying capacity model， the vegetation carrying capacity per km2 of sand-fixing plants in the study area is as follows： Pinus sylvestris var. mongholica 56 600-181 900， Salix matsudana Koidz. 72 000-192 600， Elaeagnus angustifolia L. 192 100-486 000， Haloxylon ammodendron （C. A. Mey.） Bunge 105 000-387 500， Hippophae rhamnoides L. 274 900-628 700 and Caragana korshinskii Kom. 118 500-377 300 trees per km². In conclusion， this study provided a theoretical basis for ecological restoration and sustainable land management in the agro-pastoral ecotone.Keywords：the agro-pastoral ecotone of Northern China;MaxEnt;vegetation carrying capacity;suitability evaluation;sand-fixing vegetation55|23|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To explore the hydrophilicity and hydrophobicity characteristics of biochar and their determining factors， biochars were obtained from six typical feedstocks under three pyrolysis temperatures and washed using two methods including acid-alkali washing and water washing. The contact angles of different biochars and their relation to biochar properties were analyzed by using sessile drop method and random forest analysis. The results showed that： 1） The biochar pyrolyzed at 300 ℃ was hydrophobic with contact angles greater than 120°， whereas the biochar at 700 ℃ was hydrophilic with contact angles less than 60°. The contact angles of biochar pyrolyzed at 500 ℃ varied with feedstock type： Those from sawdust， rice husk， and chicken manure were greater than 120° while those from maize straw， cow dung， and pig manure were less than 60°. 2） The results of random forest analysis revealed that the pore volume， dissolved organic carbon， specific surface area， and H content were significantly related to biochar contact angle. 3） As the pyrolysis temperature increased， dissolved organic carbon and H decreased while the pore volume and specific surface area increased， leading to the conversion of biochar from hydrophobic to hydrophilic. 4） Acid-alkali washing and water washing both decreased the biochar hydrophobicity. In conclusion， the low-temperature and high-temperature pyrolyzed biochars exhibit distinct hydrophobicity and hydrophilicity， respectively， and water washing has application potential in reducing biochar hydrophobicity.Keywords：biochar;washing treatment;hydrophilicity;hydrophobicity47|20|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To systematically investigate the effects of biogas slurry application on soil-plant interactions， tomato variety ‘Provence’ was taken as the research object. A pot experiment were conducted with six treatments： T1 treatment （V （water）∶V （biogas slurry） = 1∶1）， T2 treatment （V （water）∶ V （biogas slurry） = 2∶3）， T3 treatment （V （water）∶ V （biogas slurry） = 1∶2）， T4 treatment， （V （water）∶ V （biogas slurry） = 2∶5）， T5 treatment （full application of biogas slurry）， and CK （no biogas slurry，distilled water only） （CK）. The effects of different concentrations of biogas on tomato growth， nutrient uptake， soil properties and soil microbial community were determined. The results showed that： 1） Under the biogas slurry application treatments （T1-T5）， the aboveground dry matter weight of tomato ranged from 3.97 to 5.05 g， while the dry matter content of CK was 3.97 g. The aboveground dry matter under different biogas slurry treatments was higher than that of CK. The contents of total nitrogen and total phosphorus in shoots under different treatments were significantly higher than CK （P<0.05）， and the contents of total nitrogen and total phosphorus in shoots under T5 biogas slurry treatment were the highest， which were 32.66 and 4.26 g/kg， representing increases of 67.90% and 51.57%， respectivley. 2） Under T3 and T5 treatments， the soil conductivity increased with the increase of biogas slurry concentration， and the variation ranged from 156 to 746 μS/cm. After biogas slurry application， the soil pH decreased significantly （P<0.05）. The contents of nitrate nitrogen， available phosphorus and available potassium in soil increased significantly with the increase of biogas slurry concentration， and the increase of nitrate nitrogen content was the most significant （P<0.05）. The nitrate nitrogen content was the highest under T5 treatment， reaching 337.4 mg/kg （P<0.05）. The contents of sodium ion， potassium ion， chloride ion and sulfate ion in soil increased significantly with the increase of biogas slurry concentration （P<0.05）， and the content was the highest at the original concentration. 3） The application of original biogas slurry significantly increased the activities of leucine aminopeptidase （LAP）， β-N-Acetylglucosaminidase （NAG） and acid phosphatase （AP） in the soil （P<0.05）. 4） PCoA analysis revealed that the soil bacterial diversity using the original biogas slurry was significantly higher than that of the control， and the bacterial community composition differed significantly compared to other treatments （P<0.05）. In summary， adding biogas slurry to soil can increase tomato biomass and soil nutrient content. Among them， applying raw biogas slurry can enhance soil enzyme activities related to nitrogen and phosphorus cycling， increase soil bacterial abundance， and improve bacterial community composition. This study provided an important theoretical basis for the scientific application of biogas slurry in tomato growth.Keywords：biogas slurry;tomato;soil;bacterial community structure48|28|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：This study investigated the effects of the wide-ridge narrow-bed planting mode on the microclimate， yield， and quality of greenhouse tomatoes. Two structurally identical and uniformly managed plastic greenhouses in Wenzhou， and Zhejiang Province was selected as experimental objects. The experimental greenhouse adopted the wide-ridge narrow-bed planting mode， while the control greenhouse adopted the traditional planting mode. The photosynthetically active radiation （PAR） within the crop canopy， air temperature， soil temperature， and carbon dioxide concentration were continuously monitored in both greenhouses to analyze their effects on tomato yield and quality. The results showed that the daily average soil temperature on the west side of the wide-ridge narrow-bed greenhouse was 0.9 °C higher than that of the traditional mode and remained 0.3‑0.6 °C higher under both sunny and cloudy conditions. At 50 cm above the canopy， the PAR peak values under the wide-ridge narrow-bed mode were 37.1% and 35.4% higher than those under the traditional mode on sunny and cloudy days， respectively， and the cumulative PAR increased by 13.7%， indicating a more uniform and stable light distribution. Compared with the traditional planting mode， the average yield and single-fruit weight per plant increased by 20.7% and 31.8%， respectively. The wide-ridge narrow-bed mode enhanced surface radiation absorption and optimized canopy light distribution， and achieved the coordinated improvement of the root-zone thermal and canopy light environments and significantly increased tomato productivity. Overall， this planting mode effectively improved the greenhouse thermal‑light environment and yield performance， and provided a theoretical base and practical references for efficient and mechanized tomato cultivation in southern Zhejiang.Keywords：tomatoes;Wide trench and narrow bed;plastic greenhouse;environmental factor49|20|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To explore the effects of different LED red and blue light quality ratios and foliar zinc fertilizer types on the growth， quality and mineral element absorption of hydroponic lettuce under artificial light plant factory conditions， ‘Italian non-heading lettuce’ （Lactuca sativa L.） was used as the test material. Three treatments were set up with LED red and blue light quality ratios of 3∶1 （high red light， 3R1B）， 1∶1 （equal red and blue light， 1R1B）， and 1∶3 （high blue light， 1R3B）， all with a light intensity of 200 μmol/（m²·s）. Three types of zinc fertilizers， namely zinc sulfate （ZnSO₄）， nano-zinc oxide （nano-ZnO）， and zinc glycinate （ZnGly）， were foliar sprayed at a concentration of 1.54 mmol/L， with deionized water （ddH₂O） spray as the control （CK）. The results showed that： 1） When the same type of foliar zinc fertilizer was sprayed， with the increase of the blue light ratio， the fresh weight， dry weight and plant height of the lettuce above ground gradually decreased； while the contents of chlorophyll a， chlorophyll b and total chlorophyll in the leaves gradually increased. Compared with 3R1B， the contents of chlorophyll a， chlorophyll b and total chlorophyll in the 1R3B treatment increased by an average of 30.9%， 36.5% and 32.1%， respectively. The contents of soluble sugar， soluble protein， flavonoids and total phenols also significantly increased， with an average increase of 28.6%， 24.1%， 107.2% and 89.3%， respectively. 2） Under the same light quality （1R1B）， the fresh weight and dry weight of the aboveground and underground parts of lettuce in the nano-ZnO treatment were significantly higher than those in the ZnSO₄ and ZnGly treatments. Among them， the fresh weight and dry weight of the aboveground part of lettuce in the 3R1B treatment with nano-ZnO were 4.4 and 1.9 times higher than those in the CK treatment， respectively. Compared with CK， the foliar spraying of the three types of zinc fertilizers could significantly increase the nitrate content in lettuce， while the contents of soluble sugar and soluble protein decreased. Under 1R1B， the Zn content in the leaves of lettuce sprayed with the three types of zinc fertilizers was significantly higher than that in the CK treatment. Under 1R1B， the Zn content in the leaves of the nano-ZnO treatment was 41.4 times that of the CK treatment. However， the contents of Mg， Mn and Fe in the leaves were significantly reduced by 68.3%， 73.2% and 59.7%， respectively. 3） Meanwhile， the interaction between the red and blue light quality ratio and the type of foliar zinc fertilizer could significantly affect the fresh weight and dry weight of the above-ground leaves， the fresh weight and dry weight of the underground roots， plant height， root length， as well as the contents of nitrate， soluble sugar， soluble protein， flavonoids， total phenols， Ca， Mg， Zn， Mn， Fe and B. Therefore， under artificial light plant factory conditions， the high blue-light sources can significantly improve the pigment and quality indicators of lettuce， while the high red-light ratio can significantly increase the yield of lettuce. The yield and Zn content of lettuce foliar sprayed with nano-ZnO were higher than those of other zinc fertilizers， and the effect was better under high red-light ratio. Moreover， foliar spraying of nano ZnO could effectively alleviate the antagonistic effects of Zn ions on Ca， Fe and Mn mineral ions.Keywords：plant factory with artificial light;nano-ZnO;red and blue light;quality;mineral elements46|25|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：In order to systematically analyze the biological characteristics of ‘Korla fragrant pear’ in the process of cross pollination， with a focus on the specific effects of different pollination varieties on the fruit quality of ‘Korla fragrant pear’， and screening suitable pollination varieties， 10-year-old ‘Korla fragrant pear’ was used as test material. The effects of pollen biological characteristics and fruit quality of five pollination varieties （self-pollination and natural pollination as control） were compared， and correlation analysis and comprehensive evaluation were carried out based on quality indicators. The results showed that in terms of pollen characteristics， the number of single flower anthers of ‘Dangshansuli’ was the highest， reaching 28. The pollen germination rate of ‘Lyu’ reached 91.35% at 6 h， and the fruit setting rate was 28.40%， which was significantly higher than that of other combinations （P<0.05）. In terms of external quality， the vertical diameter and transverse diameters and fruit weight of naturally pollinated fruits increased significantly （P<0.05）， followed by the fruit weight and transverse diameter of ‘Lyu’ pollinated fruits. The hardness of ‘Yali’ pollinated fruit increased significantly to 6.92 kg/cm2 （P<0.05）， and the hardness of ‘Lyu’ pollinated fruit decreased significantly to 5.3 kg/cm2 （P<0.05）. In terms of internal quality， the contents of soluble solids and total polysaccharide in ‘Kucheamute’ pollinated fruit significantly increased， reaching 14.82% and 7.84% （P<0.05）， respectively. The titratable acid content of ‘Lvli’ pollinated fruit decreased significantly， which was 0.24% （P<0.05）. The vitamin C content of ‘Aksujujuli’ pollinated fruit increased significantly， reaching 565.15 mg/100 g （P<0.05）. In addition， ‘Dangshansuli’pollination can significantly improve fruit coloration （P<0.05）. Correlation analysis showed that peel L* was significantly positively correlated with peel b* and peel c*， and significantly negatively correlated with peel a*. Peel a* was significantly positively correlated with flesh a*， flesh b* and flesh c*. Fruit transverse diameter was significantly negatively correlated with soluble sugar content and fruit hardness. There was a significant negative correlation between titratable acid content and vitamin C content. The comprehensive evaluation showed that the ‘Lyu’ pollination treatment has the highest comprehensive scorewas and is suitable as the pollination tree of Korla fragrant pear. This study provides a theoretical basis for the improvement of yield and quality of ‘Korla fragrant pear’.Keywords：‘Korla fragrant pear’;pollination;fruit quality;principal component analysis;comprehensive evaluation39|18|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To explore the phenotypic trait diversity of Hippeastrum germplasm resources， 149 Hippeastrum germplasm accessions were used as experimental materials， 22 phenotypic traits were measured. Comprehensive evaluation was conducted using diversity index， correlation analysis， principal component analysis （PCA）， and cluster analysis to systematically assess genetic diversity and ornamental trait variation， reveal phenotypic differentiation patterns， and identify superior germplasm.The results indicate that for the 149 Hippeastrum germplasm accessions， the mean coefficients of variation （CV） for qualitative and quantitative traits were 42.02% and 24.30%， respectively， while the Shannon diversity indices （H'） ranged from 0.54 to 1.04 for qualitative traits and 1.40 to 2.09 for quantitative traits. Correlation analysis demonstrated varying degrees of association among the 22 phenotypic traits. Hierarchical clustering classified the germplasm into six distinct groups： tall-robust， slender-tall， small-petaled， large-petaled， slender-dwarfand dwarf-compact types. Principal component analysis revealed that the first five principal components cumulatively explained 65.412% of the phenotypic variation， effectively capturing the majority of morphological diversity. Based on ornamental evaluation using the membership function method， the comprehensive evaluation scores （F-values） ranged from -6.06 to 5.64，correspond to ‘Lovely Nymph’， ‘Cherry Nymph’， ‘Benito’， ‘Velvet Nymph’， ‘Marilyn’， ‘Spartacu’， ‘Stargazer’， ‘Ru You’， ‘Micui Ninghong’ and ‘Naranja’，including two elite breeding lines. This study lays a foundation for systematically analyzing the superior variation characteristics of germplasm resources， and can screen excellent candidate breeding parents based on various germplasm traits， thereby providing a theoretical basis for germplasm innovation.Keywords：Hippeastrum;germplasm resources;phenotypes traits;diversity;comprehensive evaluation75|21|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：The study was to analyze the effects of wheat-sorghum dietary crude protein （CP） on the growth performance， protein deposition， plasma biochemical indicators， and liver protein metabolism of medium-growing yellow-feathered broilers aged from 31 to 60 days， and to determine their dietary crude protein requirements total of 900 31-day-old medium-growing ephedra chickens were randomly divided into five CP level groups （16%， 17%， 18%， 19% and 20%）， with 6 replicates in each group and 30 broilers in each replicate. The experimental period was 30 d. After the experiment， the growth performance of broilers in different groups was counted. The protein deposition rate of broilers with average body weight was determined every repeat. Two broilers per replicate with average body weight were selected for slaughter sampling， and the biochemical indexes of plasma and liver protein metabolism were determined. The changes of mRNA expression level of protein metabolism key gene in liver were detected by RT-PCR. The results showed as follows： 1） With the increase of dietary CP level， the average daily gain （ADG）， body weight and the body protein content all showed linear and quadratic changes （P＜0.05）， and the ratio of feed to weight （F/G）， the daily protein deposition and protein deposition rate showed quadratic changes（P＜0.05）. Compared with 16% CP group， 18% CP group significantly increased the body protein content， daily protein deposition， and protein deposition rate （P＜0.05）. Compared with 18% CP group， the ADG and 60-day-old weight of 19% and 20% CP group decreased significantly （P＜0.05）， and the F/G increased significantly （P＜0.05）. The daily protein deposition and protein deposition rate in 20% CP group were significantly decreased （P＜0.05）. 2） With the increase of dietary CP level， the plasma total protein content and insulin-like growth factor-1（IGF-1） of broilers showed linear and quadratic changes （P＜0.05）. Compared with 16% CP group， the content of total protein in plasma of 18% CP group was significantly increased （P＜0.05）. Compared with the 18% CP group， the plasma IGF-1 content in the 20% CP group decreased significantly （P＜0.05）. 3） The mRNA expression levels of IGF-1， mammalian target protein of rapamycin， ribosomal protein kinase 1 and recombinant human eukaryotic translation initiation factor 4E-Binding protein 1 in the hepatic of 18% CP level group was significantly higher than that in 16% CP level group and 20% CP level group（P＜0.05）. In summary， a wheat-sorghum-based diet with 18% CP level could enhance the growth performance and body protein deposition of medium-growing ephedra chickens from 31 to 60 days of age by improving plasma and liver protein metabolism. The study enhances the breeding efficiency of medium-growing ephedra chickens by promoting precision nutrition technology and optimizing feed resource utilization， while also contributing to the conservation of grain resources.Keywords：medium-growing ephedra chickens;crude protein;growth performance;protein metabolism;protein deposition32|21|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To enhance milk production and nitrogen utilization efficiency， this study conducted a systematic assessment of the impact of feed nutrition regulation on dairy cow production performance and nitrogen utilization through meta-analysis. Based on 58 collected papers and 242 observation data， the study evaluated the effects of optimizing feed composition， reducing crude protein （CP） in the diet， adding rumen-protected amino acids to the diet， and using feed additives on standard milk （FPCM）， nitrogen utilization efficiency （NUE）， and nitrogen excretion. The results showed that： 1）Over the past 40 years， milk yield per lactating cow in China has been increasing year by year， yet production efficiency remains lower than that in developed countries. NUE was low， and total nitrogen excretion increased annually. 2）The four feed optimization strategies significantly improved the NUE of lactating cows（P＜0.05）， with an average increase of 4.6%. The nitrogen excretion rate was significantly reduced by 2.1%（P＜0.05）， but there was no significant effect on the dry matter intake （DMI）（P＞0.05）. The addition of high-quality forage increased FPCM by 1.3% and raised N excretion by 1.6%. Reducing dietary CP by 2% to 3% significantly boosted NUE by 12.7%， reduced N excretion by 4.2%， and stabilized FPCM， with urinary N and fecal N decreasing by 24.1% and 5.8%， respectively. Rumen-protected methionine and lysine increased milk yield by 2.0% and reduced N excretion by 8.1% （urinary N： -41.7%； fecal N： -13.0%）. Microbial additives in feed increased FPCM by 5.2% and NUE by 12.8%. 3）It is predicted that after implementing feed nutrition regulation strategies nationwide in 2050， the total milk production of dairy cows will increase by 2.147 million tons and nitrogen excretion will decrease by 0.11 million tons. In summary， scientific regulation of feed nutrition can simultaneously improve milk performance and nitrogen use efficiency of dairy cows simultaneously， reduce nitrogen emission from the source， and provide technical and theoretical basis for the construction of green production system of lactating cows.Keywords：meta-analysis;feed regulation;lactating cow;nitrogen use efficiency;nitrogen excretion39|14|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：This study aimed to elucidate the role and mechanisms by which optimized water-saving drinking bowls reduce wastewater and fecal contamination and improve pen cleanliness in large-scale pig farming.48 finishing pigs weighing （81.82 ± 7.72） kg were selected to conduct comparative trials between conventional and modified water-saving drinking bowls and shelter pens. The results showed that： 1） The transformation of the water-saving drinking bowls had no significant effect on the production performance， water intake， or drinking behavior of finishing pigs （P＞0.05）. 2） Compared to traditional Group Ⅰ， modified Group Ⅰ reduced water consumption and water waste by 12.67% and 69.52%， respectively. 3） The fecal deposition rates on traditional Group Ⅱ and modified Group Ⅱ cement floors were 19.01% and 11.08%， respectively. Compared to traditional Group Ⅱ pens， modified Group Ⅱ reduced fecal deposition on cement floors by 41.71% and ammonia （NH₃） emissions by 33.52%. In summary， by using water-saving drinking bowls and avoidance barriers， the source reduction of wastewater， feces， and NH₃ can be achieved， and the synergistic reduction of mitigating manure and harmful gas pollution in pig farming can be achieved.Keywords：pigs;water-saving bowls;dodge barriers;defecation behavior;pen cleaning25|18|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：Accurate individual sheep identification and daily behavior monitoring are fundamental for achieving intelligent sheep farming and improving animal welfare. Deep learning techniques based on sensor data have been widely investigated for sheep identification and behavior recognition. However， there are still problems such as challenges remain， including limited feature extraction capability， poor model generalization， and insufficient research on lightweight model deployment. This paper reviews and analyzes recent research in this field and proposes new approaches for optimizing deep learning-based sheep identification and behavior monitoring. The findings indicate that： 1） The high similarity among individual sheep and complex environmental conditions are major factors limiting recognition accuracy. Enhancing the feature extraction ability of deep learning models is a primary solution. In addition to expanding datasets through data augmentation and improving model performance with attention mechanisms， future research may focus on multi-modal information fusion， transformer architectures， and federated learning to further boost feature extraction and generalization. 2） When developing lightweight models suitable for edge deployment， in addition to optimizing parameters and modules during training， techniques such as pruning and knowledge distillation can be applied to compress trained models， enabling the development and deployment of real-time sheep monitoring systems on embedded devices. In conclusion， analyzing and optimizing deep learning models for sheep identification and behavior monitoring is essential for constructing lightweight， edge-deployable， and real-time portable deep learning solutions.Keywords：sheep;recognition;daily behavior detection;deep learning41|20|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To enhance the behavior responses of service providers in manure returning and address the “last mile problem” in establishing green planting-breeding cycle agriculture， this study utilizes micro-level survey data from the green planting-breeding cycle agriculture pilot program. Multiple machine learning methods， including penalized regression， ensemble learning， and deep learning were used to systematically identify the factors influencing the behavior responses of service providers in manure returning. The research showed that： 1） Compared with traditional multiple linear regression， machine learning methods can significantly improve the trustworthiness and interpretability of model results. Economic incentives， fixed assets， operating income， economic benefit cognition， and service radius are the key factors affecting the behavior response of service providers in manure returning， all of which exert significant positive impacts. 2） Through Accumulated Local Effects （ALE） plots and SHapley Additive exPlanations （SHAP） value polynomial fitting dependence plots， it was found that there are obvious non-linear relationships between three factors： fixed assets， economic incentives， and service radius， and the behavior response of service providers in manure returning. Among them， the fitting curves of fixed assets and service radius present an inverted U-shaped pattern， while that of economic incentives shows a U-shaped pattern. 3） The interaction effect between fixed assets and economic incentives can significantly enhance the behavior response of service providers in manure returning. When the stock of fixed assets exceeds 2.5 million yuan， the positive effect of economic incentives on service providers is significantly strengthened， with SHAP values increasing from below 0.3 to 0.5-1.0. 4） The interaction effect between service radius and operating income also significantly promotes the behavior response of service providers in manure returning. When the service radius covers 10 to 30 villages， service providers with high operating income can more efficiently convert the expanded coverage into economies of scale benefits， thereby improving their willingness to supply services. Based on these findings， this study puts forward the following policy recommendations： Implementing tiered economic incentive policies based on asset scale and service radius， promoting the layout of integrated regional crop-livestock farming， optimizing the manure transportation network， and strengthening the capacity building of service providers.Keywords：green planting-breeding cycle;service providers in manure returning;behavior response;machine learning35|20|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：This study aimed to estimate the profit contributions and reasonable distribution ratios of feed production， pig farming， and slaughtering & meat processing， which are the three core segments， across the entire hog industry chain under different scenarios. The Shapley value method is employed to construct a profit distribution model for the full hog industry chain to reveal the dynamic patterns of interest changes among stakeholders in the context of price fluctuations. The results show that： 1） Industry chain integration helps to stabilize returns and improve risk resistance. After the integration of the whole industry chain， the profits of normal hog price， high hog price and low hog price increased by 22.78%， 95.78% and 67.65% respectively. 2） Hog farming is the most sensitive to the fluctuation of market price， which changes from a loss of 6.70 billion yuan under low hog price to a profit of 13.02 billion yuan under high hog prices. 3） The whole industry chain can release the profits of high value-added segments and enhance their value-added potential， while the cost-saving segments have a relatively limited response. Under different circumstances， the profit increase before and after the cooperation of slaughtering and meat link is the highest， the highest is 1 958.35%， and the lowest is 230.32%； However， the feed production link only realizes the profit increase in the year of high pig price， and the rest of the years all show negative growth. Based on these findings， this study proposes the following policy recommendations：Improving the benefit distribution mechanism of the industry chain and optimize the mode of cooperation， strengthening the financial support system and enhance the risk-resistant ability of enterprises， promoting the empowerment of digital technology to promote the efficient synergy of the industry chain， strengthening the government’s macro-control and policy guidance to stabilize the market expectations， and focusing on the construction of a matrix of high-value-added products to promote the value chain to the deeper extension depth.Keywords：entire pig industry chain;Shapley value method;pig cycle management;benefit distribution24|18|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：Aiming at the problems that traditional manual rice quality inspection is time-consuming， labor-intensive， and prone to poor consistency in results due to inspectors’ subjectivity and regional evaluation standards， making it difficult to meet large-scale and standardized detection needs， a machine vision-based rice appearance quality inspection system was developed for grade classification in accordance with national standards. The system first preprocesses images by converting them to grayscale with a weighted-average method and removing noise via median filtering. It then segments and individualizes individual grains with fixed-threshold segmentation and Watershed algorithm. Finally， phenotypic parameter extraction and quality grades are determined with the YOLOv8s model. A total of 100 sets of rice samples （143 grains per set） were divided into one training set （70 sets）， one validation set （20 sets）， and one test set （10 sets）. With manual inspection results as the control， the appearance quality of the rice samples was inspected and graded. The results showed that： 1） Manual inspection yielded a head rice rate of 59.8%， brown rice rate of 78.1%， moldy grain rate of 4.32%， chalkiness rate of 11%， and graded the rice as Grade 2 indica rice. The vision system returned 59.1%， 77.3%， 4.2%， and 12%for the corresponding indicators， respectively， with the same grade， confirming a high consistency in core indicators. 2） The system matched the manual method grade in 93 of 100 samples， achieving an average accuracy of 93%. In conclusion， this system effectively improves detection efficiency and precision， and can be widely applied in scenarios such as batch detection in grain reserves， online monitoring in rice processing enterprises， and screening in agricultural scientific research and breeding.Keywords：rice;quality detection system;machine vision;YOLOv834|16|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To reveal the development trajectories and future trends of digital agriculture research in China and abroad， based on 6 293 high-quality literatures in the field of digital agriculture in China National Knowledge Infrastructure （CNKI） and Web of Science （WOS） database from 2002 to 2024， bibliometric analysis was conducted using CiteSpace 6.2.R6 software for visual econometric analysis. The results showed that： 1） Global interdisciplinary discipline presents a profound imbalance between strong coupling of technological ecosystems and weak participation of the humanities and social sciences. The deep integration of agronomy and information science constitute the main axis of technology， but the contribution of social science is significantly insufficient， and the dominant mode of hardware R&D further restricts the process of algorithm innovation. 2） The domestic and foreign integration paths form a significant cascade differentiation. Foreign research has achieved the closed-loop technology integration of perception-decision-execution earlier， while the domestic China’s hardware technology has been in the stage of transplantation for a long time， and the deep collaboration between algorithm and agronomic mechanism exhibits obvious hysteresis. 3） The driving force mechanism shows fundamentally differences. Domestic China’s policy-oriented research forms the characteristics of deep integration of agronomy science and economics， and the high-frequency emergent words mainly reflect the national strategic traction. International research highlights the market-driven technological innovation path， but neither domestic nor abroad research has cultivated cross-research clusters suitable for small-scale operation. 4） Systematic development gaps are concentrated in three dimensions， including the theoretical separation between micro-agronomic processes and intelligent decision-making models， the institutional absence of digital inclusion of small farmers， and the synergy gap between climate-smart agriculture and carbon metering technology. Future research should deepen the exploration of theory and practice integration， fully support the high-quality development of China’s agricultural and rural modernization by strengthening international cooperation and knowledge sharing， innovating digital technologies to drive agricultural transformation mode， building a multi-dimensional collaborative differentiated development path， and systematically integrating the multiple compound values of digital agriculture.Keywords：digitization;agriculture;rural area;farmer;CiteSpace;bibliometric analysis;visualization31|17|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To clarify the evolutionary trajectory and frontier dynamics of research on China’s vegetable industry economics， based on the China National Knowledge Infrastructure （CNKI） database， literature information related to the vegetable industry economics indexed in CNKI from 2000 to 2024 was mined using CiteSpace software， with quantitative and qualitative analysis methods integrated for visual presentation. The results indicated that： 1） The number of publications on the economic research of China’s vegetable industry exhibits periodic fluctuations and is largely driven by policy influence. 2） There are many scholars and research institutions， but the cooperation between scholars and research institutions needs to be strengthened. 3） Research hotspots are concentrated in four main areas， the development of vegetable production patterns， the evolution of circulation models， the mechanisms of price formation and fluctuation， and industrial development and transformation. The focus has gradually shifted from the consumption side toward circulation and production domains. Future research should strengthen the systematic exploration of policy mechanisms， focus on key issues for greening， high-efficiency and digitalization of the vegetable industry， and promote interdisciplinary collaboration and paradigm innovation.Keywords：vegetable industry economics;bibliometrics;CiteSpace;keyword co-occurrence;visualization39|21|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：This study uses the CFPS 2016‐2022 panel data and a panel fixed-effects probit model to investigate how Internet use affects rural land transfer in China， and the mechanism and heterogeneity were also analyzed. The key findings are： 1） Internet use significantly promotes land inflows but has no clear effect on land outflows； 2） The result of mechanism analyses discovered that the internet use promoted rural mainly through information access， social interaction， and non-agricultural employment； 3） Heterogeneity analysis revealed that the effect was stronger among younger， better-educated farmers， and in economically developed eastern regions； 4） Internet use also facilitated simultaneous land inflows and outflows. In conclusion， improving rural Internet infrastructure and promoting digital inclusion can support the market-oriented development of land transfer.Keywords：internet usage;importance of internet perception;internet usage frequency;land inflows;land transfer37|15|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：In order to reveal the complex causal relationship between agricultural digital transformation and county agricultural economic growth， the qualitative comparative analysis method and necessary condition analysis method are used to explore the logic of digital transformation paths of agricultural economic growth in different counties. The study found that： Firstly， two distinct configurational pathways are identified for achieving high county-level agricultural economic growth： pathway S1， which enhances the value-added of agricultural products by optimizing the agricultural industrial structure， and pathway S2， which creates high-value-added products and services by promoting the integration of agricultural industries. Secondly， government financial investment， government policy support and agricultural digital production play a central role in the process of realizing county agricultural economic growth in the combination of agricultural digital transformation conditions. Thirdly， the combination of industrial structure optimization and agricultural digital management and industrial integration development show a certain complementary relationship. At the same time， there may be policy resource competition between government financial input and policy support and industrial integration development and industrial structure optimization. Deepen the understanding of the inherent laws in the process of agricultural digital transformation to promote the growth of county agricultural economy. In policy formulation， we should promote diversified agricultural digital transformation model and choose suitable agricultural economic growth path according to local conditions.Keywords：county-level regions;agricultural economic growth;agricultural digital transformation;configuration analysis;necessary condition analysis26|16|1<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：This study aims to investigate the relationship between planting inertia， grain policies， and green transformation in grain production. Using the statistical data from 26 Chinese provinces from 2004 to 2023， this study empirically examines the impact of planting inertia on the green transformation of grain production， as well as the moderating effect of grain policies. The results indicate that： Planting inertia has a significant inhibitory effect on the green transformation of grain production. The price support policy for grain reinforces the inhibitory effect of planting inertia on the green transformation of grain production. In contrast， grain subsidy policies， high-standard farmland construction policies， and innovative insurance policies can facilitate the green transformation of grain production through multiple mechanisms， including incentives for green production behaviors， investments in green infrastructure， and risk mitigation for green investments. Furthermore， the restraining effect of planting inertia on the green transformation of grain production exhibits heterogeneous characteristics depending on regional economic development levels and regional innovation capacities. Accordingly， the study proposes the following recommendations： strengthening the hierarchical and structural design of green policies， accelerating collective action among farmers for green production practices， increasing investment in regional green infrastructure for grain production， and promoting the deep integration of grain green industry chains and innovation chains by taking advantage of the situation.Keywords：food production;green transformation;planting inertia;food policy27|16|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To clarify the research hotspots and trends in agricultural trade under China-US trade frictions since China joined the WTO in 2001， based on the theory of scientific knowledge mapping， the CiteSpace software was used to conduct a visual analysis of 468 relevant papers on agricultural trade under China-US trade frictions from 2001 to 2024 in the CNKI database. The results showed that： 1） The characteristics of publications in this field closely align with phase changes in China-US economic and trade relations， which can be divided into three periods as follows： exploration of trade liberalization （2001-2007）， prominent friction （2008-2017）， and full-scale conflict and transition （2018-2024）. 2） There are many scholars and research institutions， but their collaborative relationships still need strengthening. 3） Key hotspots include current status and trade structure analysis， impact mechanisms and effects analysis， and China’s agricultural trade problem diagnosis and response strategies in agricultural trade under China-US trade frictions. 4） Emerging trends include focusing on deepening impact mechanism studies in agricultural trade under China-US trade frictions， integrating sustainability issues， and refining model applications. In summary， despite the fruitful progress in research on agricultural trade under China-US trade frictions， future research should enhance scholar-institution collaboration， and pay more attention to the deepening of the impact mechanism， integration of sustainable development issues， and innovation of research methods.Keywords：China-US trade frictions;agricultural trade;CiteSpace;research trends30|18|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：To optimize the financial support environment for agricultural technology innovation and achieve the coordinated development of agricultural technology and finance， based on the reflections on the theoretical connotation and historical logic of agricultural science and technology finance in China， this study systematically sorts out the current situation and constraints of the coordinated development of agricultural science and technology finance in China. The science and technology finance policies introduced by China were qualitatively analyzed. The results indicate that China’s agricultural science and technology finance still faces practical difficulties such as structural supply-demand mismatch， fragmented support system， and imbalanced policy tools. It is urgent to coordinate policy creation and practical implementation， and strive to form a virtuous cycle pattern of “technology-industry-finance” in the agricultural field.Keywords：science and technology finance;agricultural technology innovation;policy innovation;collaborative development35|18|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
- Abstract：Based on the 2008-2023 panel data of 30 Chinese provinces （Data do not include those of Xizang， Hong Kong， Macao and Taiwan regions）， this study adoptes undesired super-efficiency Slacks-Based Measure （SBM） model combined with GML （Global-Malmquist-Luenberger） index to measure the agricultural green total factor productivity （AGTFP）. Two-way fixed effect model and mediation effect model are used to analyze the AGTFP， an empirical test of the impact of the development level of agricultural insurance on AGTFP and its mechanism. The results show that： 1） The development level of agricultural insurance has a significant positive effect on AGTFP. For every 1% increase in per capita premium income， AGTFP increases by 0.029%， and this conclusion is still robust after solving the endogeneity problem. 2） Mechanism analysis shows that agricultural technology progress and fertilizer application intensity are two important transmission paths for agricultural insurance to enhance AGTFP. 3） Heterogeneity analysis shows that in non-grain-producing areas and medium-high natural risk areas， agricultural insurance has a more prominent impact on green production and a more significant role in promoting AGTFP. Accordingly， this study puts forward three policy suggestions that include strengthening the top-level design to improve the efficiency of green coverage of agricultural insurance， optimizing financial incentives to promote technological progress and fertilizer reduction， and focusing on regional characteristics to improve the accuracy of insurance policy implementation.Keywords：agricultural insurance;agricultural green total factor productivity;SBM-GML model;fertilizer application intensity42|22|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-05-06
